Towards the utilization of normalized LMS algorithm in adaptive filter - Misbah Emhammed, Misbah Abdelsalam; Ho, Yih Hwa (International Organization of Scientific Research, 2014)
The latest trends in reducing the environmental noise related issues have received extra attention recently. The empirical studies reasoned this to the rapid growth in using technology in everyday things which in turn led to continues use of machines supported by noisy engines. Most of these machines results a high speed wind buffeting in which it effect the environment and people. Therefore, studies on reducing engine noise have become the main era where an alternative suggestions is still needed. In this paper, we focused on how the development of algorithms helped reduce the level of noise. This in turn led us to utilize the Least Mean Square (LMS) and Normalized Least Mean Square (NLMS) algorithms in order to do so. MATLAB was used for simulating the adaptive filter with a noisy tone signal and white noise signal. The analysis was mainly concentrated on the adapted algorithms’ performance. This study provides the insights necessary for considering other filtering mechanisms based on the normalized least mean square.